Exploring metformin monotherapy response in Type-2 diabetes: Computational insights through clinical, genomic, and proteomic markers using machine learning algorithms-Reference-Cited by-同舟云学术

Exploring metformin monotherapy response in Type-2 diabetes: Computational insights through clinical, genomic, and proteomic markers using machine learning algorithms

Published:2024-03 Issue: Volume:171 Page:108106
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Villikudathil Angelina Thomas^ORCID,Mc Guigan Declan H.^ORCID,English Andrew^ORCID

Funder

Ulster University - Magee Campus

Publisher

Elsevier BV

Reference54 articles.

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4. Sulfonylureas as second line drugs in type 2 diabetes and the risk of cardiovascular and hypoglycaemic events: population based cohort study;Douros;BMJ,2018

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1. Computational approaches for clinical, genomic and proteomic markers of response to glucagon-like peptide-1 therapy in type-2 diabetes mellitus: An exploratory analysis with machine learning algorithms;Diabetes & Metabolic Syndrome: Clinical Research & Reviews;2024-07

2. Computational Approaches for Clinical, Genomic and Proteomic Markers of Response to GLP-1 Therapy in Type-2 Diabetes Mellitus: An Exploratory Analysis With Machine Learning Algorithms.;SSRN Electronic Journal;2024